Mobile data transmission is continuously increasing with use of smart phone and tablets. Therefore, to meet the users demand, network operators have to increase the network capacity and to scale the mobile data network effectively. However, traditional cellular systems may have some limitations in its architecture. Such limitations may include scalability issue under dynamic load conditions, fault tolerance, and utilization issues. Typically, a base station (BS) has dynamic load as the number of user equipment (UEs) in a coverage area is dynamic and the service use by such UEs is also dynamic. So, the base station (BS)/Baseband Unit (BBU) need to have capability to handle maximum load. Over a longer period of time this maximum load also keeps increasing with the increase in subscriber base and increased number of connected devices. Further, if a BBU goes down, the coverage gets affected. It is not a cost effective solution to have additional physical BBU as a backup always. Further, due to dynamic load, at any moment, some of the BBU may be overloaded and the rest may be relatively idle leading to imbalance in resource (computing, network) usage. This could lead to a lot of waste of processing resources and waste of powers at idle times.
In order to overcome the continuous scalability issue, one option is to move the computation intensive portion of the BBU, inter-BBU communication and backhaul onto Cloud platform, such as Cloud-Radio Access Network (Cloud-RAN or C-RAN). For adaptive network scaling and efficient resource utilization under dynamic load conditions, network virtualization and reuse of network resource is essential. However, scheduling of packets in the C-RAN is not effective as the packets are scheduled on predefined priorities assigned to them.